Mitchell Nathan Professor, Learning Sciences PhD, 1991, University of Colorado-Boulder Room 1019 Educational Sciences Building Phone: (608) 262-0831 STAAR Lab: (608) 263-0563 Fax: (608) 262-0843 Email: mnathan@wisc.edu

Prof. Nathan received his Ph. D. in experimental (cognitive) psychology. He also holds a B.S. in electrical and computer engineering, mathematics and history. He has worked in research and development in artificial intelligence, computer vision and robotic mobility, including: design and development of autonomous robotic arms and vehicles; the development of expert systems and knowledge engineering interview techniques; and the representation of perceptual and real-world knowledge to support inference-making in dynamic environments. Nathan also has worked on computer-based tutoring environments for mathematics education that rely heavily on students' own comprehension processes for self-evaluation and self-directed learning (so-called unintelligent tutoring systems). He has affiliate appointments in the Department of Curriculum & Instruction and the Department of Psychology.

RESEARCH STATEMENT
“I currently study how students reason quantitatively, and how their intuitions (such as invented strategies) about quantitative relations can serve as the basis for learning topics such as formal algebraic strategies. My work on student cognition includes the study of learning of mathematics and science as it occurs in career and technical education settings (a.k.a. vocational education) that can contribute to the development of effective engineering practices.

I also study teachers' beliefs about the development of students' mathematical reasoning, how expert blind spot among educators with high levels of mathematics training may influence teachers' views of development, and how technology that supports video case analysis and professional discourse and reflection can facilitate teacher change and professional development. My work with teachers includes those who primarily teach academic courses, and those who primarily with in technical education (pre-engineering and engineering) settings.

My research is largely rooted in cognitive, embodied and social aspects of learning and teaching behavior in and out of classrooms. I employ quantitative and qualitative research methods, such as experimental design, survey design, think aloud reports, design based research, and verbal and gesture-based analyses of learner and teacher discourse.

My work is directed at both basic research on intellectual performance and learning, and applications of that work to curriculum development, teacher education and staff development.

I am currently co-Principal Investigator for the ELViS Project (Enhancing Learning with Visual Scaffolding) funded by the U. S. Dept. of Education-Institute of Educational Sciences (IES) for 2006-2009. This project investigates how mathematics teachers use visual scaffolding, including pointing, gestures, diagrams, objects, and other methods, and explores whether and how such methods of highlighting visual information influence students’ learning of abstract concepts and mathematical representations.

I am also Co-Principal Investigator for the AWAKEN Project (Aligning educational experiences with ways of knowing engineering) sponsored by the National Science Foundation Engineering Education Program (NSF-EEP) for 2007-2010. This project seeks to foster a more diverse and more able pool of engineers in the United States by understanding the pre-engineering experiences of K-12 students, document the expectations that K-12 teachers in academic and vocational settings have for engineering preparation, and relate these to post-secondary learning experiences and the actual professional work experiences of practicing engineers.”

REPRESENTATIVE PUBLICATIONS:
Nathan, M. J. (in press). An embodied cognition perspective on symbols, grounding, and instructional gesture. In DeVega, M., Glenberg, A, M. & Graesser, A. C. (Eds.) Symbols, Embodiment and Meaning: A Debate (pp. 375-396). Oxford, England: Oxford University Press.

Koedinger, K. R., Alibali, M., & Nathan, M. J. (2008). Trade-offs between grounded and abstract representations: Evidence from algebra problem solving. Cognitive Science, 32(2), 366 - 397.

Alibali, M. W. & Nathan, M. J. (2007). Teachers' gestures as a means of scaffolding students' understanding: Evidence from an early algebra lesson. In Goldman, R., Pea, R., Barron, B. J., and Derry, S. (Eds.) Video Research in the Learning Sciences (pp. 349-365). Mahwah, NJ: Erlbaum.

Nathan, M. J., Eilam, B. & Kim, Suyeon (2007). To disagree, we must also agree:  How intersubjectivity structures and perpetuates discourse in a mathematics classroom. Journal of the Learning Sciences, 16(4), 525-565.

Nathan, M. J. & Kim, Sunae (2007). Pattern generalization with graphs and words: A cross-sectional and longitudinal analysis of middle school students’ representational fluency. Mathematical Thinking and Learning, 9(3), 193-219.

Nathan, M. J. & Jackson, K. (2006). Reframing the role of Boolean classes in qualitative research from an embodied cognition perspective. In S. Barab, K. Hay, & D. Hickey (Eds.) Proceedings of the International Conference on the Learning Sciences (pp. 502-508). Mahwah, NJ: Erlbaum.

Koedinger, K. R. & Nathan, M. J. (2004). The real story behind story problems: Effects of representations on quantitative reasoning. Journal of the Learning Sciences, 13(2), 129-164.

Nathan, M. J. & Petrosino, A. J. (2003). Expert blind spot among preservice teachers. American Educational Research Journal. 40(4), 905-928.

Nathan, M. J., and Koedinger, K. R. (2000). Teachers’ and researchers’ beliefs about the development of algebraic reasoning. Journal for Research in Mathematics Education, 31, 168-190.

Nathan, M. J., Kintsch, W., & Young, E. (1992). A theory of algebra word problem comprehension and its implications for the design of computer learning environments. Cognition and Instruction, 9(4). 329-389.